Manthan Patel recently shared something that caught my attention: "Most automation tools are built for one team. But repetitive tasks exist everywhere." That simple observation is the real story behind a lot of failed automation efforts. We buy a tool for Sales, or Finance, or IT, then act surprised when the rest of the company keeps copying and pasting data between apps like it is 2012.

In his post, Manthan described testing one tool across five departments using the same approach each time: "Write what you want in plain English. The system figures out which apps to connect, asks you to authenticate them, and builds the workflow." No drag-and-drop flowcharts. No configuring brittle "if this then that" rules. You describe the outcome and it handles the wiring.

That is a big claim, and it is also the direction the market is moving: from workflow builders that require a specialist to agent-like automation that any operator can initiate.

The real bottleneck: automation has been designed like software, not like work

Traditional automation platforms are powerful, but they are optimized for builders, not for doers.

If you have ever tried to automate something simple like a weekly revenue email, you know the routine:

Pick an app connector (Stripe, HubSpot, Google Sheets)
Read docs to find the right fields and scopes
Create API keys or OAuth apps
Test payloads
Handle edge cases (missing values, duplicates)
Maintain it when one app changes a field name

Most teams quit somewhere around step two.

Manthan framed the barrier clearly: "The barrier to automation has always been technical complexity. This approach removes it." If the tool can translate intent into integrations, the bottleneck shifts from engineering knowledge to process clarity.

"If your task has steps and touches multiple apps, it can be automated." - Manthan Patel

That line is optimistic, but directionally correct. The more important implication is this: if automation can be described, it can be attempted. And that changes adoption.

Why plain-English automation matters across departments

Manthan pointed out that repetitive work is not confined to one team:

Sales has follow ups
Finance has reports
Operations has approvals
IT has the same alerts every week

I would add support, recruiting, and marketing ops to that list without blinking.

The cross-functional opportunity is huge because most of the friction in modern work sits between tools, not inside them. The moment a task spans multiple apps, humans become the glue. Glue does not scale.

Here is the practical value of a plain-English builder: it lowers the cost of experimenting. Instead of needing an automation engineer for each workflow, teams can try small automations and keep the ones that stick.

Examples of high-ROI, low-drama workflows

If you want to pressure-test whether this approach is real, start with workflows that have three properties: clear trigger, predictable steps, and measurable output.

Sales

Trigger: inbound demo request
Steps: enrich lead, create CRM record, assign owner, send a personalized follow up, schedule reminders
Output: speed-to-lead and meeting rate

Finance

Trigger: weekly schedule
Steps: pull Stripe revenue, categorize refunds, update a sheet, email a summary
Output: time saved and fewer reporting errors

Operations

Trigger: new vendor request form
Steps: validate fields, route approval, create a purchase request, notify requester
Output: shorter cycle time

IT and security

Trigger: recurring alert type
Steps: open ticket, attach logs, check status pages, notify on-call
Output: fewer manual triage steps

Manthan shared two concrete wins: he automated a weekly revenue summary from Stripe in under 10 minutes, and a CRM follow up sequence even faster. Those are exactly the kinds of workflows that prove value quickly.

The underrated breakthrough: guided app connections and credentials

The part of Manthan's post I think most people will gloss over is the app connection experience. He said the tool tells you exactly which credential to grab and where to find it: paste it in, done.

That matters because integrations fail at the seams:

Someone does not have admin access
The API key is created with the wrong permissions
OAuth consent screens are misconfigured
Tokens expire and nobody notices

A tool that guides credential selection is not just a UX improvement. It reduces the hidden cost of setup, and it makes automation feasible for non-technical operators while still keeping authentication explicit.

What to watch out for: removing complexity also removes visibility

When tools hide wiring, you gain speed but you can lose understanding. If you are adopting AI-driven automation, you need guardrails.

1) Data access and least privilege

If a workflow connects CRM + email + billing, it can accidentally expose sensitive data. Treat credentials as production assets:

Use service accounts where possible
Limit scopes to only what is required
Rotate keys and log access

2) Approval gates for high-impact actions

A plain-English request like "cancel any overdue subscription" is powerful and dangerous. Add human approvals for:

payments and refunds
account deletions
outbound email at scale
permission changes

3) Observability: logs, retries, and ownership

Automations that no one owns become silent failures.

Require a named owner per workflow
Track run history and error states
Set alerts when failure rates spike

Speed is only a win if reliability follows.

A simple checklist for deciding what to automate first

Manthan ended with a question: "What repetitive task would you hand off first?" If you are not sure, use this quick filter:

Frequency: happens daily or weekly
Standardization: the steps are mostly the same each time
Multi-app: requires copying info between tools
Measurable: you can quantify time saved or errors reduced
Low regret: failure is annoying, not catastrophic

If a task scores high on 1-4 and low on 5, it is an ideal starter automation.

My recommended first automation for most teams

Start with a weekly executive summary that pulls from the systems you already use (Stripe, CRM, support desk) and sends a short email or Slack message.

Why? Because it is:

easy to verify (numbers either match or they do not)
valuable immediately (everyone likes clarity)
low risk (it reports, it does not change data)

Once that is stable, move to workflows that take action, like CRM follow ups or approvals.

Where Turbotic Automation AI fits in

Manthan named the tool he tested: Turbotic Automation AI, and he shared a link for anyone who wants to try it: https://lnkd.in/ebbRi76H.

I am less interested in any one product than I am in the pattern his post highlights: automation is shifting from building diagrams to declaring outcomes. If that holds, the winners will be the teams that learn to describe their processes clearly, set guardrails, and iterate fast.

If you take one lesson from Manthan Patel's post, it is this: repetitive work is not a department problem. It is an organizational tax. Plain-English automation is one of the first credible ways to reduce that tax without turning every team into a mini engineering org.

This blog post expands on a viral LinkedIn post by Manthan Patel, I teach AI Agents and Lead Gen | Lead Gen Man(than) | 100K+ students. View the original LinkedIn post →